File size: 1,227 Bytes
6e3369e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained("PATH_TO_MODEL", device_map="auto", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("PATH_TO_MODEL", trust_remote_code=True)
# For PEFT models (if not merged)
# from peft import PeftModel
# model = PeftModel.from_pretrained(model, "PATH_TO_MODEL")
# Prepare input
system_prompt = "You are embodying the following persona: [PERSONA]"
user_prompt = "Survey Question: [QUESTION]\n\nPlease provide your honest and detailed response to this question."
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt}
]
# Tokenize input
input_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(model.device)
# Generate response
with torch.no_grad():
outputs = model.generate(
input_ids=input_ids,
max_new_tokens=256,
temperature=0.7,
top_p=0.9,
do_sample=True
)
# Decode response
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
|